In X-ray imaging, particularly in the medical field, methods are frequently used in which the object to be observed, in particular the body of a patient, is irradiated with two different X-ray spectra in order to be able to better represent different tissue types, for example. The X-ray images generated with these different X-ray spectra are usually combined with one another for the representation. An X-ray imaging technique also referred to as “split-filter” or “twin-beam dual-energy” computed tomography is optionally used here. In this case, a beam filter is introduced into the beam path between the X-ray source and the X-ray detector, which beam filter splits the X-ray beam into two beam ranges (or: partial beams), which are respectively assigned to one of the two X-ray spectra.
The X-ray detector is in this case illuminated area-by-area with the different X-ray spectra. These areas of the X-ray detector are usually arranged adjacent to one another, viewed in the direction of travel of a patient table (also referred to as a patient couch). Choosing a suitable pitch (a ratio of the table travel per revolution of the X-ray source and the slice thickness to be examined) ensures that the same slice of the object (i.e. of the patient) is scanned with both spectra during a spiral scan, there being a time offset of usually one gantry rotation between the two images generated with the different X-ray spectra. As a result of the time offset, the examination objects within the respective slice (for example, the heart, blood vessels and other organs) recorded via the respective detector area may have moved significantly.
Due to such movements, differences can occur between the images captured with the two detector areas, which differences can lead to image artifacts when the two images are analyzed together with so-called dual-energy algorithms (for example, a so-called base material decomposition). While it is known in the field of X-ray imaging for images captured under different conditions to be registered to one another, i.e. in particular for the structures of one image to be deformed such that they match the corresponding structures of the other image and consequently overlay these, these methods, too, can reach their limits, in particular if movements within the areas of the image differ sharply locally.
From printed publication DE 0 2009 007 236 A1 a method for scanning a moving examination object with a CT system is known, in which data is recorded during a rotating movement of a transmitter/receiver pair about the examination object. Furthermore, sectional images of the examination object are determined from the data via an iterative algorithm, motion information relating to motion of the examination object during the data recording being included in the iterative algorithm.
From printed publication DE 10 2011 007 529 A1 a method, a radiation therapy system and a combination of CT system and radiation therapy system for determining a motion profile of a moving object in an examination object with an emitter-detector system displaceable relative to the examination object are known, the following method steps being executed:
scanning of the examination object in the region of the moving object during a displacement of the emitter-detector system relative to the examination object and generation of a pixel data set with attenuation values over time,
removal of fixed structures from the pixel data set,
determination of an attenuation value induced by the moving object in each detector row at a plurality of successive time points of the scan and formation of a 3D data set from the values of the attenuation maximum of the detector rows over the detector rows and the readout times of the scan, and
determination of at least one of the values from the following list from the result data set: frequency and/or phase and/or amplitude of the motion of the object, area of location of the object during the scan, position of the object at a predefined phase of the motion.
From printed publication DE 10 2011 083 647 A1 a method for generating a motion-compensated CT image data set is known, wherein:
a projection data set of a CT system is recorded from a predefined motion phase and a projection angle range, which projection data set allows the reconstruction of a CT image data set,
the motion field is determined iteratively by:
multiple reconstruction of the one CT image data set with a first image resolution with a motion-compensating reconstruction method using a first analytical reconstruction algorithm and different motion fields from each of a plurality of location-specific motion vectors,
and determination of the motion field using at least one predefined constraint,
and reconstruction of a final CT image data set with a second image resolution using a motion-compensating reconstruction method based on a second reconstruction algorithm and the determined motion field.